A Novel Vaccination Strategy Mediating the Induction of Lung-Resident Memory CD8 T Cells Confers Heterosubtypic Immunity against Future Pandemic Influenza Virus
Bibliographic record
Abstract
The currently used vaccine strategy to combat influenza A virus (IAV) aims to provide highly specific immunity to circulating seasonal IAV strains. However, the outbreak of 2009 influenza pandemic highlights the danger in this strategy. In this study, we tested the hypothesis that universal vaccination that offers broader but weaker protection would result in cross protective T cell responses after primary IAV infection, which would subsequently provide protective immunity against future pandemic strains. Specifically, we used tandem repeat extracellular domain of M2 (M2e) epitopes on virus-like particles (M2e5x VLP) that induced heterosubtypic immunity by eliciting Abs to a conserved M2e epitope. M2e5x VLP was found to be superior to strain-specific current split vaccine in conferring heterosubtypic cross protection and in equipping the host with cross-protective lung-resident nucleoprotein-specific memory CD8(+) T cell responses to a subsequent secondary infection with a new pandemic potential strain. Immune correlates for subsequent heterosubtypic immunity by M2e5x VLP vaccination were found to be virus-specific CD8(+) T cells secreting IFN-γ and expressing lung-resident memory phenotypic markers CD69(+) and CD103(+) as well as M2e Abs. Hence, vaccination with M2e5x VLP may be developable as a new strategy to combat future pandemic outbreaks.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".